1. Neuroscience
Download icon

Chimpanzee brain morphometry utilizing standardized MRI preprocessing and macroanatomical annotations

  1. Sam Vickery  Is a corresponding author
  2. William D Hopkins
  3. Chet C Sherwood
  4. Steven J Schapiro
  5. Robert D Latzman
  6. Svenja Caspers
  7. Christian Gaser
  8. Simon B Eickhoff
  9. Robert Dahnke  Is a corresponding author
  10. Felix Hoffstaedter  Is a corresponding author
  1. Research Centre Jülich, Germany
  2. MD Anderson Center, United States
  3. The George Washington University, United States
  4. Georgia State University, United States
  5. University of Jena, Germany
  6. Jena University Hospital, Germany
Research Article
  • Cited 3
  • Views 1,319
  • Annotations
Cite this article as: eLife 2020;9:e60136 doi: 10.7554/eLife.60136

Abstract

Chimpanzees are among the closest living relatives to humans and, as such, provide a crucial comparative model for investigating primate brain evolution. In recent years, human brain mapping has strongly benefited from enhanced computational models and image processing pipelines that could also improve data analyses in animals by using species-specific templates. In this study, we use structural MRI data from the National Chimpanzee Brain Resource (NCBR) to develop the chimpanzee brain reference template Juna.Chimp for spatial registration and the macro-anatomical brain parcellation Davi130 for standardized whole-brain analysis. Additionally, we introduce a ready-to-use image processing pipeline built upon the CAT12 toolbox in SPM12, implementing a standard human image preprocessing framework in chimpanzees. Applying this approach to data from 194 subjects, we find strong evidence for human-like age-related gray matter atrophy in multiple regions of the chimpanzee brain, as well as, a general rightward asymmetry in brain regions.

Data availability

The T1-weighted MRI's can are available at the National Chimpanzee Brain Resource Website as well as the direct-to-download dataset we used for our example workflow.The code used in the manuscript can be found at this GitHub repo https://github.com/viko18/JunaChimp

Article and author information

Author details

  1. Sam Vickery

    Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
    For correspondence
    s.vickery@fz-juelich.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6732-7014
  2. William D Hopkins

    MD Anderson Center, Bastrop, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Chet C Sherwood

    Department of Anthropology, The George Washington University, Washington, DC, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6711-449X
  4. Steven J Schapiro

    MD Anderson Center, Bastrop, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Robert D Latzman

    Psychology, Georgia State University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1175-8090
  6. Svenja Caspers

    Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
    Competing interests
    The authors declare that no competing interests exist.
  7. Christian Gaser

    University of Jena, Jena, Germany
    Competing interests
    The authors declare that no competing interests exist.
  8. Simon B Eickhoff

    Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6363-2759
  9. Robert Dahnke

    Department of Neurolgy; Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
    For correspondence
    robert.dahnke@uni-jena.de
    Competing interests
    The authors declare that no competing interests exist.
  10. Felix Hoffstaedter

    Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
    For correspondence
    f.hoffstaedter@fz-juelich.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7163-3110

Funding

Helmholtz Association (Helmholtz Portfolio Theme 'Supercomputing and Modelling for the Human Brain)

  • Sam Vickery
  • Simon B Eickhoff
  • Felix Hoffstaedter

Deutsche Forschungsgemeinschaft (417649423)

  • Robert Dahnke

European Commission Horizon 2020 (945539 (HBP SGA 3))

  • Sam Vickery
  • Simon B Eickhoff
  • Felix Hoffstaedter

Helmholtz Association (Initiative and Networking Fund)

  • Svenja Caspers

European Commission Horizon 2020 (785907 (HBP SGA 2))

  • Svenja Caspers

National Institutes of Health (NS-42867,NS-73134,NS-92988)

  • William D Hopkins

National Institutes of Health (NS092988)

  • Chet C Sherwood

James S. McDonnell Foundation (220020293)

  • Chet C Sherwood

Inspire Foundation (SMA-1542848)

  • Chet C Sherwood

National Institutes of Health (U42-OD011197)

  • Steven J Schapiro

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: The chimpanzee imaging data were acquired under protocols approved by the Yerkes National Primate Research Center (YNPRC) at Emory University Institutional Animal Care and Use Committee (Approval number YER2001206).

Reviewing Editor

  1. Jonathan Erik Peelle, Washington University in St. Louis, United States

Publication history

  1. Received: June 17, 2020
  2. Accepted: November 20, 2020
  3. Accepted Manuscript published: November 23, 2020 (version 1)
  4. Version of Record published: December 8, 2020 (version 2)

Copyright

© 2020, Vickery et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,319
    Page views
  • 101
    Downloads
  • 3
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

  1. Further reading

Further reading

    1. Neuroscience
    Lorenz Deserno et al.
    Research Article Updated

    Dopamine is implicated in representing model-free (MF) reward prediction errors a as well as influencing model-based (MB) credit assignment and choice. Putative cooperative interactions between MB and MF systems include a guidance of MF credit assignment by MB inference. Here, we used a double-blind, placebo-controlled, within-subjects design to test an hypothesis that enhancing dopamine levels boosts the guidance of MF credit assignment by MB inference. In line with this, we found that levodopa enhanced guidance of MF credit assignment by MB inference, without impacting MF and MB influences directly. This drug effect correlated negatively with a dopamine-dependent change in purely MB credit assignment, possibly reflecting a trade-off between these two MB components of behavioural control. Our findings of a dopamine boost in MB inference guidance of MF learning highlight a novel DA influence on MB-MF cooperative interactions.

    1. Developmental Biology
    2. Neuroscience
    Qiuling Li et al.
    Research Article Updated

    Although many genes are known to influence sleep, when and how they impact sleep-regulatory circuits remain ill-defined. Here, we show that insomniac (inc), a conserved adaptor for the autism-associated Cul3 ubiquitin ligase, acts in a restricted period of neuronal development to impact sleep in adult Drosophila. The loss of inc causes structural and functional alterations within the mushroom body (MB), a center for sensory integration, associative learning, and sleep regulation. In inc mutants, MB neurons are produced in excess, develop anatomical defects that impede circuit assembly, and are unable to promote sleep when activated in adulthood. Our findings link neurogenesis and postmitotic development of sleep-regulatory neurons to their adult function and suggest that developmental perturbations of circuits that couple sensory inputs and sleep may underlie sleep dysfunction in neurodevelopmental disorders.